{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import the dataset from csv file and read through pandas.\n",
    "iris = pd.read_csv('iris.csv', delimiter = ',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(150, 5)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Examine the shape of the dataset: 150 rows, 5 columns.\n",
    "iris.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 150 entries, 0 to 149\n",
      "Data columns (total 5 columns):\n",
      "sepal_length    150 non-null float64\n",
      "sepal_width     150 non-null float64\n",
      "petal_length    150 non-null float64\n",
      "petal_width     150 non-null float64\n",
      "species         150 non-null object\n",
      "dtypes: float64(4), object(1)\n",
      "memory usage: 5.9+ KB\n"
     ]
    }
   ],
   "source": [
    "# Number of instances and how many attributes in the dataset. \n",
    "# Demonstrates a complete dataset - no null values.\n",
    "iris.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "species\n",
       "setosa        50\n",
       "versicolor    50\n",
       "virginica     50\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Number of instances of each species shows a balanced dataset - each type is equally represented.\n",
    "iris.groupby('species').size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "      <th>species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>4.4</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>6.1</td>\n",
       "      <td>2.8</td>\n",
       "      <td>4.7</td>\n",
       "      <td>1.2</td>\n",
       "      <td>versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>7.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>4.7</td>\n",
       "      <td>1.4</td>\n",
       "      <td>versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>6.9</td>\n",
       "      <td>3.1</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.1</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>5.6</td>\n",
       "      <td>2.7</td>\n",
       "      <td>4.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>7.1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.9</td>\n",
       "      <td>2.1</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>6.4</td>\n",
       "      <td>3.2</td>\n",
       "      <td>4.5</td>\n",
       "      <td>1.5</td>\n",
       "      <td>versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>5.5</td>\n",
       "      <td>2.6</td>\n",
       "      <td>4.4</td>\n",
       "      <td>1.2</td>\n",
       "      <td>versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>4.9</td>\n",
       "      <td>2.4</td>\n",
       "      <td>3.3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>5.6</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>1.5</td>\n",
       "      <td>versicolor</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     sepal_length  sepal_width  petal_length  petal_width     species\n",
       "42            4.4          3.2           1.3          0.2      setosa\n",
       "73            6.1          2.8           4.7          1.2  versicolor\n",
       "50            7.0          3.2           4.7          1.4  versicolor\n",
       "139           6.9          3.1           5.4          2.1   virginica\n",
       "94            5.6          2.7           4.2          1.3  versicolor\n",
       "102           7.1          3.0           5.9          2.1   virginica\n",
       "51            6.4          3.2           4.5          1.5  versicolor\n",
       "90            5.5          2.6           4.4          1.2  versicolor\n",
       "57            4.9          2.4           3.3          1.0  versicolor\n",
       "66            5.6          3.0           4.5          1.5  versicolor"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Sample look at the dataset.\n",
    "iris.sample(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>150.000000</td>\n",
       "      <td>150.000000</td>\n",
       "      <td>150.000000</td>\n",
       "      <td>150.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5.843333</td>\n",
       "      <td>3.054000</td>\n",
       "      <td>3.758667</td>\n",
       "      <td>1.198667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.828066</td>\n",
       "      <td>0.433594</td>\n",
       "      <td>1.764420</td>\n",
       "      <td>0.763161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>4.300000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>5.100000</td>\n",
       "      <td>2.800000</td>\n",
       "      <td>1.600000</td>\n",
       "      <td>0.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>5.800000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>4.350000</td>\n",
       "      <td>1.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.400000</td>\n",
       "      <td>3.300000</td>\n",
       "      <td>5.100000</td>\n",
       "      <td>1.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>7.900000</td>\n",
       "      <td>4.400000</td>\n",
       "      <td>6.900000</td>\n",
       "      <td>2.500000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       sepal_length  sepal_width  petal_length  petal_width\n",
       "count    150.000000   150.000000    150.000000   150.000000\n",
       "mean       5.843333     3.054000      3.758667     1.198667\n",
       "std        0.828066     0.433594      1.764420     0.763161\n",
       "min        4.300000     2.000000      1.000000     0.100000\n",
       "25%        5.100000     2.800000      1.600000     0.300000\n",
       "50%        5.800000     3.000000      4.350000     1.300000\n",
       "75%        6.400000     3.300000      5.100000     1.800000\n",
       "max        7.900000     4.400000      6.900000     2.500000"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Basic statistical features of the dataset as a whole.\n",
    "iris.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 804.75x720 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Initial visual observation of the measurements and relationships between them.\n",
    "sns.pairplot(iris, hue = 'species') \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Swarmplots here and below show the distribution of measurements by species.\n",
    "sns.swarmplot(x = 'species', y = 'sepal_length', data = iris)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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bGVqtNpVSqiZcdByDiIy40OvGmKUX2LcH1qWhQKyzkznGmGdE5BlgvTFmgYg8j5UQSoGzwAPGmJ0X+pk6jkEppaqvxge4icgLxpjfXqysNmhiUEqp6vPGALerPZRdV439LztbjmSxLz3XVnboTB4/pGVSMeGezStm3cGztnEIRaVlrD94llM59nEItdWm8oLCbDi0EgqzfB2JugBjDFtPb+Vw9mFb+YGsA2w7s41q3l9zWapKH8MDwINAWxHZXOGlKGCFtwLzZ7lFpUx6Yw0bD2cCcFOvlkwf34un/ruVd1db/9k6NY/i/Z8NZOnuU/x23haKSx00jAjmzcn9iAgJZNIba0nPKSIoQJg2tgs390motTal4gx+qmbs+Ro+uhuKcyG4Adw2E5J/4uuoVCVZRVnc99V97DxrXa0elzyOaYOm8cTyJ1iwbwEA3Zt05/WrXycyJNKXofpUVW5XfR/4Ange+H8VynOMMWe9EpWf+2DNYdfBFuCTTcdISWrsOoAD7DyRwxvL9/PemsMUl1rT+mbml/Dnz3cSFRZEeo7Vf1/qMDz3+U6yCkqq1uay/by3tqptlrq1eXtKIoPbN/HCb6WeW/RbKykAlORZ25oY/M77O953JQWAubvn0rlxZ1dSANhyegsf7f6IKd2m+CJEv1CVxBAIZAMPVX5BRBrXx+RwLKvArWzvKfdLNWkZBWRWGp9wLKuAqCL7rKkFJWUcqjC4rebazPMQu06h4RVZRy+8rfzCifwTbmX7Mve518tzr1efVKWPIRVY7/w3HWt08h7n81Tvhea/xvRoQUCFqzFRoUHcO7QNsQ1CbPVu7ZPAiGT7mIuxPVu63V7au1VDJvRP9NBmknubfX9cm1d09L8xIJeF7pXm7+9Wv+fz91fXJF1j224U2oi7utxFVHCUqyxAAtzq1TfVuStpBrDAGPO5c/s64CpjzGNejM8jf7graenudN5bfYgGoUH8bFhburSMZu+pXGYs3UdmfjG3pSRyTdfmZBeW8Mp3e9l+LJvhHeK4Z2gbAgTeWX2Ir3econ1cJA9d0Y7YyNBaa1N5QUkhrPgnpK2GhP4w9FEIDr/4fqrWfXf4Oz7e+zHRIdHc2+1e2jZsy+6M3czcOpPcklxu73g7Q+OH+jpMr/DG7aqpxpi+lcrWV+WH1DR/SAxKKVXXVDUxVGeupNMi8iTwLtZI6DuBM5cYn1JKKT9VnXEMPwXigPnAJ0BTZ5m6RGln8ymsNCHeqZxCsjxMqKfqAEcZZByEsvq9kHxdcCr/FDnFObayrKIsThectpUVlRVxNLf+3UhQ5TMG591Hj3gxlnoj7Ww+P3t7PTtP5BATHszzt3Tnys5NeeSDTSzadoLgQOHeoW35f9d18nWoqqqOpMKcSZB9FKJawu2zILG/r6NSleSX5PPrpb9m2dFlhASE8LMeP2Nqz6n8a8O/eGvbW5Q6ShmVOIq/jPgLy44sY9rKaWQXZ9O+YXv+NepfJEYl+vot1IqLnjGIyIvOfxeKyILKD++HePn586Kd7DxhfVvJKijh/83bzHtrDrNom3WLXEmZYcbSfWw4nOHLMFV1fPqIlRQAco7Bwkd9G4/y6MNdH7Ls6DIAih3FvLLpFb448AX/t+X/KHVYZ3rfpn3LnF1zeHrV02QXWyss7s3cy/TU6T6Lu7ZV5YzhHee/f/NmIPXJvkrjE7ILS9l21H0ahb0nc+nTqlFthaV+jPTd9u3Tu3wTh7ogT2MWNpzc4Fa2/cx2sorsf5P7M/d7LS5/c9EzBmPMubEKgcA6Y8zSig/vhnd5GtXJvtpah6aRbuMQQoICGNpBRyjXGcmV7ntPvtZzPeVTIxLtk0WHB4VzW/JthAaG2spHtxlNh0YdbGXDE4d7PT5/UZ27kiYDM0TkDLDM+VhujNHrHdX06FXJAHyz4xTtm0by22s70So2gr+O68G7qw8RHhLIz0d1oGVDvQ++zrjhXxDeCNLWWH0LV/2vryNSHlzd+mqeGvgUc3fPJSY0hgd6PkBy42RevfJVXtv8GnkleYzvOJ5hCcNo27At01Onsy9zH8MThvNQL7fJHy5bVR7H4NpBpCUwDvg10NIYU53kUiN0HINSSlVfjY9jEJE7gWFAd+A08DLWWYNSSqnLSHW+7b8I7ANmAN8ZYw56JaLLVHGpw7amM0BJmYPgQHtZaZmDABECKkxyZIyhzGEIqlTXU5uqlhgDjlIItE9eSGkxBNnnt6KsBAKCQKc794mSshKCK31OpY5SAiXQNgW9wzhwGAdBAUEX3d9T2eWkykcVY0wT4B4gDHhWRNaKyDsX2a3e25SWydX/WEryk18w/rVVHM8q4ExuEXe9uZbkJ79g5F+/Y9W+MzgchqcXbKPrtC/p/cfFzFxxAIA569JI+dPXdP7DIn47dzMlZQ6PbapatPMzmN4V/tQU5twFRblweg+8PhL+FAevjbDuUirOgzl3w5+aWfV3LPR15PXKqfxT3PPlPfR5tw83fnIjP6T/QKmjlKdXPk3/9/oz4sMRzNs9D4APdn7A8A+HM+C9ATy35jnKHGWsP7GeMfPH0OfdPtz/1f2cKTjjsc3LUXXmSooGhgAjsC4pNQFWG2Pu9l54ntWVPgZjDCP/tsQ2pfY1XZsRHRbMR6lHXGVNIkP5zTUd+c28zbb9Z07pxz0z1+Go8BH9YUxnZq065Nbma5Nqfcqq+qkwC/7e2Vpz4Zyhv4RDq6wJ9M5J6AdtRsCyCnd5B4XDYzusTmrldY8teYyvDn3l2o6PjOfuLnfz3NrnXGUBEsDLo17mwW8etO07bdA0Xt30KukF6a6yG9rdQGFpoVubn9/yOQFSN87cvTFX0vIKj5eNMUcuUr/ey8wvcVtnYfORLKLD7Kegp3OLWLXfPhQf4OsdJ21JAWD9oQyPbapakr7LnhQAjqbCsUr3wh/dAKFR9rLSAji1A1oP9m6MCoCtp7fato/mHiX1pH2lAIdxsOTIErd9U0+m2pLCufYKS+3rmRzNPUpGYQax4bE1E7SfqM6lpB7GmAeNMe97Sgoi8lLNhlb3NWoQQsdm9oPDwLaxDGjb2FYW3zCcKzs1s5UFCNzQsyXBgfbr0iOS4zy2qWpJs64QFmMvSxoGrYdUKhviXhYaA817eDc+5ZLS3P7FuF1MO4bE2z+ToIAgrm9zvds3/mEJw4iPjLeV9Wvez2Obl1tSgOqdMVzMkItXqX9emdibJ+ZvZftxa+2EP4zpQnBQALmFpXy94yTtm0byzI3d6BYfw8Ezeby9ylo74dGrOtC/TSyv3NGHv3y5i8z8Ym5PSeS2von0bd3IrU1VS0IawIT3YdHvICvNWpBnyCPQayJ8+igcXgOJ/WDsP6FBU8g5AVvnQUw8XPMchNbfdYRr22/6/YbismJWHF1BcuNknhr4FG1j2pKWk8bHez4mOjSaR3o/Qp9mfXhh2Au8sukVcktyGd9xPKPbjKZtTFueXf0s+7KscQyP9nmUMlPm1ublqNrjGM7bkMgGY0yfGmnsIupKH4NSSvmTqvYx1I0eE6WUUrWmJhOD3qStlFKXgZrsY/hnDbZ12difnsu0BdvYfiyboR2a8MwN3QgKFJ5ZuJ1vdp6kXVwkT9/Qlc4topmxdB/vrDpEREggj16VzPU9WvDtzpP89cvdrj6GR6/qwIHTeW5txkRcvoNt/M7h1fDlE1YfQ9db4Cd/hLzT8PmvrdcS+8P1f4cGcbB4GmydC9HxcM2zekdSLcopzuG5Nc+x8thKkhsl8/sBvycpOokZm2cwb/c8YkJj+EXvXzAicQRfH/qaVza9Ql5JHrd3vJ37ut/Hnow9PL/2eddcSb/r/zsigiN8/bZqxUX7GERkIdZSnh4ZY26o6aAupi71MVz74veutRcAbukTT3RYMDNXHnSVJTYO53fXdebB98pveQwMEOb8z0B++voaisscrvK/jOvBm8sPuLX5j9t7efeNKEtxPkzvAgUV5o4c9RQcXgV7vy4va3sFtB0BXz9dXhYWA7/aYXVgK697asVTfLL3E9d2+4btmdJtCk8sf8JVFhwQzJvXvMnkRZMpM+WrKf51+F/518Z/kZaT5iqb0HECTwws37cuqslxDLoOwyXKyCu2HcABVu074zaOIe1sAYu3n7CVlTkM8zcetSUFgCW7TnlsU9WSk1vtSQHgwFLrTMFW9r37FBiFWXD8Bz1rqCVrj6+1be/N3Mv3ad/bykocJSzcv9CWFACWHllqSwoAa0/Y27ucVWU9hqUXetRGkHVVTHgwiY3tU2d3i4+hW7z9PvjYBiH0b2Mf2wAwsmNTt2NLn1aNPLapakmTZKh8OaFFL+thK+vpXhYUBnG6XGtt6RJrv427ZYOW9Gpq/0wEYVj8MLd9+zTtQ5Nw+3ooldu7nFW581lEOojIXBHZLiL7zz28GVxdFxAgvDi+F0mx1oGkT6uGPH1DV/7fdZ0Y3M4aFBPfMJx/TujN7SmtmDigFSGBAUSFBvHE6M5c1bkZf7qpGw0jggkKEG7pE89dg5I8tqlqSXhDuOnfENkMEOg4GoY/Dje8BM26WXWadoUbX4Fhv4JOY6x6DZpa+0W4fwFQ3vHb/r+ld9PeACRGJfLn4X9mfMfx3NjuRoIkiOiQaJ4Y8AQjE0fym36/ISo4iqCAIMYlj+OWDrfw52F/dg1y69e8H4+lPObLt1OrqjNX0nJgGjAdGAtMce4/zXvheVaX+hjAmjOpoKSMiBD7lbv84lLCg+0zPBaVlhEoYptJtbTMQanDEBYceNE2VS1xOKC0EEIqnT0U5boPYivOt84WAvTucF/IL8knPCjc/ndWVkSgBNpmUi11lFJmymyruRljKCgtuGw6nb0xjiHcGPMNVjI4ZIx5Ghh1qQHWJyLi8QAeERJk+88KEBoU6Da9dlBggC0pXKhNVUsCAtyTAnge2RwSoUnBhyKCI9z/zgJD3abXDgoIclviU0Qum6RQHdX531ooIgHAHhF5WERuBppeaAcRCXNOz/2DiGwTEbf1DkUkVEQ+FJG9IrJGRJKq9Q6UUkrVqOp85XwUiAB+AfwR62zhYlNuFwGjjDG5IhIMLBeRL4wxFW/huBfIMMa0F5EJwAvA+GrE5Tc2pWXyz693k5Ffwvh+ify0fytO5RTyl0W72H4sm2EdmvDLq5MJDBBe+nYv3zjnSnr8mo4kNIrgk41HeWe1NY7hoSvaM7BtbJXbrHxGoS6gMAu++aM1TXZCf7jyD9atpKtehi1zISYBRj0JTTvDrkWw0jk/5OCHoeN11gyr3/4RMtOg2y0w+BdQlF3zbdajhX2Ky4p5ZdMrrjEHj/Z5lLiIOD7e8zHzds8jOjSaqT2n0jOuJ6knU3l98+uu9ZnHthvL8dzj/HPjP9mfuZ9hCcOY2nMqxpg60WZwgP+NQapyYjDGrANwnjX8whiTc5FdMFYHRq5zM9j5qNypcSPwtPP5XOBlERFTU5M41ZKs/BIm/WcNOUWlgJUkGoYH8+aKA6w7aN3euP14NoUlZUSHB/PSt3sB2HYsm10ncnjy+i48+uEmV3trD5xl4cNDq9zm/97YrTbfbt228BHYNt96fmIL5KVbYw6+etIqO77Jmkr7p7Nh9h1w7lbGwyvhvm/gwzsh+2h53aBw67WabnPA/d7/XfiJ6anTeXfHuwDsPLuTQ9mHmNJtCtNWlndhbji5gfdGv8fUxVMpLLOmv/4h/Qdiw2KZvmE6O8/uBGDH2R04jIPC0sI60eYjfR6p+V/oj1Sdu5JSRGQLsBnY4rw81LcK+wWKyCbgFLDYGLOmUpV4IA3AGFMKZAF1bh7bVftPuw7g53y25bjrAH7O1ztOsXj7SVvZzhM5zN9on8m8qNTBO2sOVblNVQ07P7dv7/rcvSznOKTOLD+AAxgHbHi7/ADu2v+zarQ5y0Obszy3WY98l/adbfuH9B/48uCXtrL80nzm7J7jOtie89n+z1wH23OWpC35UW1+uv/TKrf51cGvbGX5pfnM2VX1Nv1RdfoY3gQeNMYkGWOSgIeAty62kzGmzBjTC0gA+otI5a+2ns6X3c4WROR+EVkvIuvT09M97OJbbePcOx2Tm0URFxVaqV4D2sbZR75GhQXRuUW02/59WjV0K+t4njZVNTTpYN8iN6M7AAAdeElEQVSO7eBeFhAE8R6+97TsA5VP/T3tf942PUxA3LKv5zbrkaSYJNt2bFgsHRq6/w56NHFfzyK5cTLRIfa/n6TopB/VZsfGHavcZvuG7d327x7Xvcpt+qPqJIYcY8yycxvGmOXARS8nVaifCSwBrq300hEgEUBEgoAY4KyH/V83xqQYY1Li4uKqEXbtSG4WxSNXdnAtrDOkfSz3DG3Dn2/pTky49Uef2DicJ6/vwm+v7UQ758E8KjSIZ2/uzp0DW3NVZ6svPzBAuHdoG27uneDW5pTztKmq4fp/OMchYP07ZjoM+7V10AfrMs41z1lrLPS8A+u7i0CPCdB7Ilz7vFUHrEFswx/3Tpv1yOMpj5MQmQBAdEg00wZNY2LniQxsMRCw7hi6v8f9jGk3hsldJxMk1lXw4QnDGd9xPE8NeorIYOvLWVJ0Er/s+0uftjm23dgqt+mPqjOOYTpW5/MHWN/oxwMZwDwAY8wGD/vEASXGmEwRCQe+Al4wxnxaoc5DQHdjzFRn5/MtxpjbLxSLP49jyMwvJreolIRG5be4FZaUcSyzgKTYBgQEWAd5YwwHz+TTLDrUdtvpscwCQoMCiI0MrXabqhrKSiDjIDRKgsAK39bP7oeIWPsqbTknAQNRzcvLCrMh/zQ0buvdNusRh3FwOPswzRs0JywozFV+LPcYEUERNAwrP4POKMygqKyI5g3Kf38FpQWczDtJ6+jWrttT60qbtaWq4xiqkxi+u8DLxhjjNqZBRHoAs4BArLOTOcaYZ0TkGWC9MWaBiIQB7wC9sc4UJhhjLjii2p8Tg1JK+auanEQPAGPMFdUNwhizGeuAX7n8DxWeFwK3VbdtpZRS3lHlxCAizYDngJbGmOtEpAswyBjzhteiq2dW7j3Ne2sOExESyM+GtyW5WZSvQ6pftsyFrR9b6zMPedT690gqrJkBGBgwFRJSIPsYLH8Rso5YYw66j4PSImvMwuE11noMg38OQaE/rk3lFcuOLGP+3vlEh0QzuetkkmKS2Je5j1nbZpFXkse45HEMajnI12H6VHUuJX2BdRfSE8aYns6O4o3GGPfudy+7HC8lbTycwbgZqyhzWJ9HdFgQSx6/gsYNQnwcWT2xZS7Mu7d8O7a9NeZgxlBrTiSw5jv6n+Xw4R1wend53Ztfs9ZjSJ1ZXtb7TmtNBrc2P4QZQ+xtTl1ujW2o3GbPCTX+Nuu7tcfXct9X92GcNz42DmvM7OtnM27hOLKLswEIkABmXTvLbSbWy4E35kpqYoyZAzjANeag7MK7qKpa+MNxV1IAyC4s5budOj6h1mz+0L59Zi+sea38AA7W87Uz7AdwgM1zrIet7KPztDnDvc0152lT1bjPD3zuSgoAZwvP8vb2t11JAazO5UUHF/kiPL9RncSQJyKxOMcYiMhArMFoqgY0jwl1K2sWHeahpvKKqBaVCsT6hl9Z43Yglf5solu47++pDIHYdlVvU9W4uAj3W91bR7V2rxfuf7fE16bqJIZfAQuAdiKyAngb+LlXoqqHJvRvRfcKC+5c36MFQ9rXuQHgddewX0FMK+eGwNBfQso90HZkeZ02w6HfvTDsMVzjMmMSre1rny9fwCcoHK55/jxt3lv1NlWNu6PTHbYBaTe1v4nxncZzXZvrXGWdG3fmto71+36Y6vQx3AZ8iTUY7VZgAPCUp/EL3nY59jGANbZhY1omDUKC6NhcO55rXVkJpK2F6JbQuE15+bFNgIGWFW6wO3vAmsYioT8EOfuBCjLg+GZo3r18QZ4f26aqcQ7jYHP6ZqJDomnbsHzMyJ6MPeSV5NEzrmetjy+oLd4Yx7DZGNNDRIZi3Z30d+D3xpgBPy7U6rtcE4NSSnmTNzqfz3U0Xw/MMMb8F9CvNUopdZmpznoMR0XkNeAq4AURCaV6iUUp/3ZwBWz7GKLjrev+YTHWdBbnbkPtc7fVeVyYDevfhKw06HozJA0FY6y7kA6vtsYx9JhgrdpW1TZVlZ3KP8WcXXPIK8njpvY30bFxR4rKipi7ey77M/czPGE4IxJHAPDNoW9YcWwFHRt15JYOtxAcGMz2M9tZsG8BMSEx3N7xdmLDY73SZl1WnUtJEVgT4G0xxuwRkRZYcxx9dZFda5xeSlI1bvdX8P7tuCb2bdkbxr8P/x4EhZlWWVgMPLAK5twFR8/9/xP46QdWQljxYnl7gx6GNiPc25zwPrzqoc2Y+Fp4k3Vffkk+N3xyAyfzranrQwNDef/693ll4yt8m/atq960QdMoLC3khXUvuMpGtxnNpC6TmPTFJEod1nT2CZEJvH/9+9y28LYabfOTmz5xWybUH3hjSox84OMK28eB45cWnlJ+JnUmttnej22EVa+UH8DBWvlt1SsVkgLWPqkz4dAq9/bOHvDQ5svubW772BoprS7q+yPfuw7gAEVlRczeOdt2AAc8roew6OAiQgJCXAdwgCO5R3hr61s/rs1A9zZXHVvFyMSRl/w+fU0vBSkFEOrhLrBzdxZdrCw0yn1/T2VgzbJalZ+tPGoQ7L72SHRItNvymJEhka7prc8JDQwlysPvOiY0xq2sWm2GuLfpKc66RBODUgBDHrFPi91rIgycCs0qzPjStKs1t1HvSeVloTHWvqOerDBITaxtT20O8NBmN50XqaoGtxxMv+b9XNstG7Tkzi53ck+3e1xloYGhTO0xlQd6PmA7uN/f437u6nIXTcObusqGxA/h7i5313ibKc0uerXGr1W5j8GfaB+D8or8s7D3G4hJgNbOSdRKi2Hv14CB9leXjy84vBoy06D9leVnEWf2WWMWEvpBk/bVb1NVSZmjjNXHV5NXksewhGGEOxc42n5mO/sy9zGwxUDXCOcTeSdYd2IdyY2S6di4I2D1U3x/9HtiQmIY0GIAARLglTb9UY2PY/AnmhiUUqr6vDGOQSmlVD1QnXEMStU/+WfLZzrtfhs0iLUuBW3/BDIPQ+exEGddTmD/UkhbY11Kaudc1yp9N+xYYF1K6nqLddnIU5vKKzanb2blsZV0bNSRkYkjERGO5R5j0cFFxITEcF2b64gIjiCvJI/P9n9Gfkk+17a5luYNmuMwDr49/C37MvcxNGEoXWO7+vrt1Bq9lKTU+eSfhRnDIPuItR3V0lo74ZOpsMc5fCcgGO76r3UL6+I/lO975TRoPRhmjYWyYqus3ZVw6388t6nJocYt3LeQ3y//vWv7jk53ML7jeO74/A7ySvIAa8K8mdfOZOLnE9mbuReAqJAoPhzzIW9seYN5e+YBIAh/G/E3fpL0k9p/IzWoxscxKFXvbJ1XfgAHyDlmjUPYU2FMp6MEVr9qdUZXtOKfcPyH8qQAsO8bWPmye5tbPrLugFI1aua2mbbtObvnUOoodSUFgB1nd/Dm1jddSQEgpziH97a/x/y9811lBsOs7bPqfGKoKu1jUKo6PN1tUtUyAE+zdvrpHSx1nSBu255mTT1fmaf96wv9H6nU+XQfV2E9Bax1EgY9BMnlc/cTGAoDH7TWWqho6KNW3YrTInT4CQx+2L1NXd/ZK+7pdo/tYD6h0wQmdp5IVHD5gLSusV25t+u9JDdKdpXFhMYwsfNEbulwi6ssQAKY0nVK7QTuB7SPQakLKciwLikZA91utcYslJXAjoXWJHqdxpRPgndwBaSthsQB1sR6YI1t2Pmp1fnc+QYIDPbcpvKKbWe2serYKpIbJTMsfhgiwom8E3x18CtiQmO4JukawoLCyC/J58uDX5JXksc1SdcQFxGHwzj4/sj37M3cy7D4Ya4xC3WZjmNQSillo+MYlFJKXRJNDEpdigPLYNMHkHe6vCx9F2x4x/r3nLzTVr0D31uXjpTP5Rbn8tn+z1h2ZBllDmv9sVJHKd8f+Z4vDnxBfkm+jyP0Pb1dVanq+uRB2PSe9TwkCqZ8Bie2wH8fxppmW2DsPyG+L7x1HRRlW3V7jIdbXvdV1Ao4lnuMiZ9P5HSBldAHtRjEq1e+yr1f3cuGU9by9c0bNOf90e+75kaqj/SMQanqOLOvPCkAFOdYYxa+fZbytRcMfPesVX4uKYC1wtvpPbUZrapk9s7ZrqQAsOr4KmZun+lKCmBNkvfR7o98EZ7f0MSgVHV4usxQnAcVBk2Vl3mqm+uduFSV5Je6fybZxdnu9er55SRNDEpVR/Pu1u2oLgIp90C/++z1+t0LfafYB6/Fp1jLeyqfubnDzbb1FFpFteKervfQokELV1lYYBg3tb/JF+H5Db1dVanqKsqB1FnWOIauN0OrgVbH8tZ51tQYif2tyfFE4PAa2DbfWtO5z90QFu3r6Ou9XWd3sXDfQqJDo7kt+TYahTXidMFp5u6eS15JHje2u5H2jdr7Okyv0HEMSimlbHQcg1JKqUvi1cQgIoki8p2I7BCRbSLyiIc6I0UkS0Q2OR9/8NSWUj5zZL31qOjMPti/BEqLysvyzljLeFYc21BaZNU7vRdV+3KLc1l5dCUn8066ysocZaw7sY7dGbttdXee3UnqyVQcxuEqO557nJXHVta7zmhvj2MoBR4zxmwQkSggVUQWG2O2V6q3zBgzxsuxKFU9pUXw7q1wcJm13XoI3PkxLP0zLJ9ulUW1hMmfWoPa5k6B0kJr4rxxb0CzrjBzDGQfteoO/gX85I++eS/10MZTG3nw6wfJLcklUAJ5YuATXNnqSqYsmsL+rP0AjG07lmeHPstjSx9j8aHFACQ3SubNa95k4b6F/HX9X3EYBzGhMbx21Wt0bVI/FuvxamIwxhwHjjuf54jIDiAeqJwYlPI/2z4pTwoAh1bAuv9Y4xPOyTkGy/4Oh1ZaSQGgrAi+/D20GVGeFABWvmTdvdSode3EX8+9mPoiuSXW7cFlpozp66dzLOeYKykALNy/kG5NurmSAsDujN28t+M9Zm6b6Tp7yCrK4qWNLzHj6hm1+yZ8pNb6GEQkCegNrPHw8iAR+UFEvhARjylZRO4XkfUisj49Pd2LkSrllHvSvSzjEFS41OCql3uqUtkp9zIM5On/3dpScSAbQE5JDifz3T/TtJw0t7ITeScoKC2wlaUX1J/PrlYSg4hEAvOAR40xlUeTbABaG2N6Ai8Bn3hqwxjzujEmxRiTEhdXf4eqq1rU5QYIjijfDgqHAf8DcZ3s9XpMgJ7jK5WNdy9rkgwt+3gnVuVmTDv71enhCcO5ucPNtjUaYsNiuavLXTQMbegqC5RAxiWPo3/z/rb9x7Yd692A/YjXb1cVkWDgU+BLY8w/qlD/IJBijDl9vjp6u6qqNcc2wprXAQP974f4PpBzwroslHkYut1ijWUoLYY1/7bGLST2txbvCQqxLkdtnWctyDP45xDd4qI/UtUMYwwf7f6IFUdXkNw4mcldJ9MguAErj61k/p75xITGcHeXu0mMTuRA1gHe3v42eSV53JZ8G/2a9yO7OJuZW2eyL3MfIxJH2Bbuqav8YhyDWGvmzQLOGmMePU+d5sBJY4wRkf7AXKwziPMGpolBKaWqr6qJwdt3JQ0BJgFbRGSTs+z3QCsAY8wMYBzwgIiUAgXAhAslBaWUUt7l7buSlsOFV9A2xrwMvOzNOJSqcQUZkJsOceVrBVNaBGf3Q+O2EFRhref03dCgiS7hqeoMXY9BqepaPQMW/8G6LbVZd7hzrpUQ5txl3XUU0QRunwWxHeC9cXBiszW24appMOghX0ev1EVpYlCqOnJPwVdPgqPE2j65Bb7/KxxaVX4rav5p+OwxaxzDic1WWVmRlUy63QpRzX0Tu1JVpHMlKVUdmYfLk8I5Z/bC2X2Vyva5lzlKIeOgV8NTqiZoYlCqOlr0hOgEe1mnMdDp+kpl17uXRbXUcQyqTtBLSUpVR2Aw3PWJtXRnZpp1aajffdBzAjRoCmmrIaE/jHoSQqOsDumt8yA6Hq54whrboJSf0/UYlFKqntD1GJRSSl0STQx+pqC4jKLSMl+HoS6mrNRa4rOygkz3sqIcq75SdYT2MfiJ0jIHT36ylbmpRwgNCuDhUR14YGQ7X4elPNk6Dz7/jXVbaoefwK3/gayj1noM6TuhSUcY9yY0bAXz7oM9X0FELFz3AnQf5+volbooPWPwEx9vOMrsdWmUOgx5xWW8sGgnW49m+TosVVlBBnzykJUUwDrof/9XWPBzKykAnN4FCx621mnY8yVgrPqfPAj5Z30WulJVpYnBT2w75p4EPJUpHzu9ByrN08/xzeUD2S5UVlZkrfSmlJ/TxOAnhrRvYtsODBAGto31UTTqvJp3h/BKcx61HWk9LlYW1tAaB6GUn9M+Bj/xk67NefL6zryz+hARIUE8cmUHWsc28HVYqrLgcLhjjjUtRlaatR7D4J9Dr4nwxePO9Rj6wei/WXMm5Z2GrR9DTDxc/UcIibj4z1DKx3Qcg1JK1RM6jkEppdQl0cSglFLKRhODUtW1fym8OhieT4QFv4CSQmvepHduhmdbwts3WrOwqjrj0/2fcu28axk+ezgvb3yZuniJvSZp57NS1VGUCx9OgiLnrcQbZkF0Szi0Eg4stcr2L7HGLEz+1Gdhqqo7lH2IJ5Y/gcM4AHht82u0jWnL6LajfRyZ7+gZg1LVcXJbeVI459AKKzFULlN1wsZTG11J4ZwNpzb4KBr/oIlBqepo2hlCIu1l8SmQ0M+9TNUJPZr0cCvr3qS7DyLxH5oYlKqOsGi49Q1rHiQJtNZjGP5ruPHl8uQQnwI3/du3caoqa9uwLU8NfIrGYY0JCwzjzs53MrbdWF+H5VM6jkGpS+VwQEDAxctUnWGMQUR8HYbX6DgGpbzNUwLQpFCnXc5JoTr0f7FSSikbTQxKKaVsNDEopZSy0cSglFLKRhODUkopG00MSimlbDQxKKWUstHEoJRSysariUFEEkXkOxHZISLbROQRD3VERP4lIntFZLOI9PFmTEoppS7M29NulwKPGWM2iEgUkCoii40x2yvUuQ7o4HwMAP7t/FepuqOkAJb9HQ6vhsQBMOwxXd9Z1VleTQzGmOPAcefzHBHZAcQDFRPDjcDbxpq0abWINBSRFs59laobPnsMNr1nPT+4DLLS4JbXfRuTUpeo1voYRCQJ6A2sqfRSPJBWYfuIs0ypumPrx/btbfN9E4dSNaBWEoOIRALzgEeNMdmVX/awi9uUryJyv4isF5H16enp3ghTqUvXMNG+HZPouZ5SdYDXE4OIBGMlhfeMMR97qHIEqPhXlAAcq1zJGPO6MSbFGJMSFxfnnWCVulTXvQCh0dbz0GgY/RffxqPUj+DVPgax5rB9A9hhjPnHeaotAB4WkdlYnc5Z2r+g6px2o+BXO+DUDmjaCUKjfB2RUpfM23clDQEmAVtEZJOz7PdAKwBjzAzgc2A0sBfIB6Z4OSalvCM0EhL7XbyeUn7O23clLcdzH0LFOgZ4yJtxKKWUqjod+ayUUspGE4NSSikbTQxKKaVsNDEopZSy0cSglFLKRhODUkopG00MSimlbMQaRlC3iEg6cMjXcXhRE+C0r4NQl0w/v7rrcv/sWhtjLjqnUJ1MDJc7EVlvjEnxdRzq0ujnV3fpZ2fRS0lKKaVsNDEopZSy0cTgn3Tpr7pNP7+6Sz87tI9BKaVUJXrGoJRSykYTg4+JyGQRaenrONSlE5FnROSqS9hvpIh86o2Y6isRaSkicy9hv/+ISJeL1JkqInddenR1h15K8jERWQL82hiz3texqPNzrkYoxhhHDbY5EuuzH1PF+kHGmNKa+vn1if7uqkfPGLxARBqIyGci8oOIbBWR8SLSV0SWikiqiHwpIi1EZByQArwnIptEJFxErhSRjSKyRUTeFJFQZ5t/FpHtIrJZRP7mLBsrImuc9b8WkWa+fN91gYi8ICIPVth+WkQeE5HHRWSd8/f7v87XkkRkh4i8CmwAEkVkpvMz3SIiv3TWm+n8LBGRfiKy0vnZrxWRKBEJE5G3nPtsFJErPMTVWEQ+cf781SLSo0J8r4vIV8DbtfArqjMu8FludW5PFpGPRGQh8JWIBIjIqyKyTUQ+FZHPK3xuS0Qkxfk8V0SedX6Gq8/9XTnb/7XzeXvn39wPIrJBRNqJSKSIfOPc3iIiN9b6L6WmGGP0UcMP4Fbg/ypsxwArgTjn9njgTefzJUCK83kYkAYkO7ffBh4FGgO7KD/Da+j8t1GFsvuAv/v6vfv7A+gNLK2wvR24C+tuFMH6svQpMBxIAhzAQGfdvsDiCvue+xxmAuOAEGA/0M9ZHo21SuJjwFvOsk7AYednPRL41Fn+EjDN+XwUsMn5/GkgFQj39e/O3x7n+SyHA1ud25OBI0Bj5/Y4rKWEA4DmQAYwzvlaxb9DA4x1Pv8L8GSFz+LXzudrgJudz8OACOdnHe0sa4K1XLH4+vd0KQ9vr/lcX20B/iYiL2AdZDKAbsBi64oEgcBxD/t1BA4YY3Y7t2dhLXv6MlAI/EdEPnO2CZAAfCgiLbAOSge883YuH8aYjSLS1NmvE4f12fQAfgJsdFaLBDpgHcAPGWNWO8v3A21F5CXgM+CrSs13BI4bY9Y5f1Y2gIgMxTrwY4zZKSKHgORK+w7F+kKBMeZbEYkVkRjnawuMMQU//t1fXs7zWR6uVG2xMeas8/lQ4CNjXQ48ISLfnafpYsr/xlKBqyu+KCJRQLwxZr4zjkJneTDwnIgMx/pCEQ80A078iLfpE5oYvMAYs1tE+gKjgeeBxcA2Y8ygi+zqcX1sY0ypiPQHrgQmAA9jfat8CfiHMWaB83r10zXzDi57c7G+PTYHZmOdGTxvjHmtYiURSQLyzm0bYzJEpCdwDVbCvh24p+IuWN82K7vguucXqHOurTwPrylL5c+ysoq/u6p8DgAlxvm1HyjD/Th5vnYmYiWovsaYEhE5iHU2UedoH4MXOL/B5Btj3gX+BgwA4kRkkPP1YBHp6qyeA0Q5n+8EkkSkvXN7ErBURCKBGGPM51iXlno5X48Bjjqf3+3N93SZmY2VYMdhHVi+BO5x/p4RkXgRaVp5JxFpAgQYY+YBTwF9KlXZCbQUkX7O+lEiEgR8j3XQQESSgVZYlwYrqlhnJHD63BmHuqDKn+WFLAdudfY1NMO6lFdtzs/liIjcBCAioSISgfX3eMqZFK4AWl9K+/5Azxi8ozvwVxFxACXAA0Ap8C/n5YEg4EVgG9b16RkiUgAMAqYAHzkPKOuAGVh9DP8VkTCsbyu/dP6cp511jwKrgTa18u7qOGPMNuflgKPGmOPAcRHpDKxyXurLBe7E+rZYUTzwloic+0L1u0rtFovIeOAlEQkHCoCrgFexPuMtWP8PJhtjipw/65ynnW1vBvLRRF8llT9L51ne+czDOuveCuzG6ifIusQfPQl4TUSewfobvw14D1goIuuBTVhfFOokvV1VKVVviEikMSZXRGKBtcAQY0yd6wPwNj1jUErVJ5+KSEOsmzX+qEnBMz1jUEopZaOdz0oppWw0MSillLLRxKCUUspGE4NSXuack6ehr+NQqqq081kppZSNnjEoxXlnxD3onMFzrfPR3lk3TkTmiTUb6zoRGeIsj5TyWVQ3i8itzvKDzlHTiMidzrY2ichrIhLofLjN2qqUr+g4BqUs1wLHjDHXAzhHqL8AZBtj+ou1QMuLwBjgn8B0Y8xyEWmFNaVGZ6xpMrKMMd2dbTSq+AOco6vHYw2qKhFrOu+JWCPg440x3Zz19LKT8ilNDEpZbDPiGmOWOaes+MD5+gfAdOfzq4AuFaa0iHZOy3AV1rw9gDXpXqWfcSXW1N3rnPuGA6eAhVx41lalapUmBqVwnxFXrIVxwD5b6rnnAcCgylNhi3W0v1CnnQCzjDG/c3vhwrO2KlWrtI9BKTzOiHtu5tTxFf5d5Xz+FdbU5+f27XWectulJOAbYNy5mVvFWrWtdRVmbVWqVukZg1IWTzPizgVCRWQN1peonzrr/gJ4xTkT6rlptacCf3KWb8WamfV/gY/P/QBjzHYReRLnMpPOn/MQ1iys5521VanaprerKnUezoVWUowxp30di1K1SS8lKaWUstEzBqWUUjZ6xqCUUspGE4NSSikbTQxKKaVsNDEopZSy0cSglFLKRhODUkopm/8PDPI8RvFznzoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.swarmplot(x = 'species', y = 'sepal_width', data = iris)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.swarmplot(x = 'species', y = 'petal_length', data = iris)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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4HcCvXfwazyx+hs+3fV607x/P/COH8w/z6PxHi8pGpoxkXO9xNS7m6B6jq/Tvdiw1Za4kkfph4cTA7QUvKDFU0jvr3yk62AJ8n/k9Lyx/oehgC5BbkMvkNZMDDrYAU9ZOCVo74eMtHxMbFVv1MRsGx5ywfEK5Y1ZnYigvneuKVIXYUnPyx9W9OfqrW5OYJkFloe4CSoxNDJrltGlMU5pGNw0oi42KJaH053SUmAmxCeWPGWI9hhaxwZP0HS1mTaTEIFIVzr0fzP/vZA28bamUsT3HckJ88SymQ5OHMq7XOM5oU7wkfHKTZK7pdQ03nnxjUVlcVBy3nHoLt/W9jZgGMUXlN59yM+N6jytXzJ/0+knlYvYuf8yaSH0MIlUlbSNsXwDJ/aBll0i3pk7Izstm9o7ZJMQkMLDNQMyMAlfAN6nfkJWXxZDkIcQ1jANgddpqNhzYwBltz6BVo1YA7M7ezbc7v6V78+50b969xsasLhrHICIiATSOQUREjovuShKpKpu+8sYxtB8IJ54d6dZIBWTnZTNt0zSy8rIY2XkkreNbR7pJEaXEIFIV5jwFM/5QvH3eAzDkl5FqjVRAbn4u10y7hvUH1gMwful4Xr/kdTo07VDGnnWXLiWJVIWvnwjcnv2vyLRDKuyr778qSgoAGbkZTF07NYItijwlBhERCaDEIFIVhtwduD34rtD1pMYZmjw0YLGehJgERnUfFcEWRZ76GESqwlm/gLZ91flcC8VExfDqRa8yfdN0MvMy1fmMEoNI1ek81HtIrRMfHc+V3a+MdDNqDF1KEhGRAEoMIsdj6zewbAoc2l9clrYRlr4B+zYUlx3a79Xb+k31t1HKrcAVMGfHHD7d8ik5R3LK3qGOK/elJDO7AngEaA2Y/3DOOU0jKfXLe3fCohe953GJcN002LUC3rkFXIE3id5lz0C702DCCMg54NU97SdeudQo+QX53PzJzXyz00veyU2SeeWiV6p9HqOapCJnDI8ClzrnEp1zCc65pkoKUu+kbSpOCgA56TD7CZj5Zy8pgPdz5p+9sQ2FSQHgu1cCzyakRpibOrcoKYC3nsKba9+MYIsiryKJYZdzblXYWiJSGxzOCC7LyQguD1UGXiKRGiUzN7NcZfVJmYnBzK7wLyMtMLPJZja2sMwvF6k/2p7qTatdxKDfdd6jpP7X+2VWYt++3uUlqVGGtR8WcHtqTIMYLu1yaQRbFHllTrttZi8c42XnnLuhaptUNk27LRGVkw7z/wfp26DP5dB5GBQUwJJJ3jiGDmfAqT+GBg28ifVWvAWJ7aH/z6BRs0i3XkLYlbWLyWsmk30kmx91/RE9W/SMdJPCosrXYzCzwc652WWVVQclBhGRigvHegxPlbNMRERqsfL0MQwys3uBJDO7p8TjASCqjH0nmNluM1t+lNeHm1m6mS32H1ooV6pe+vewbT7kHykuy8mALXO9n4UK8r166dsD99+10rsdtabElEpxzrFi7wq2ZWwLKN+cvpmV+1ZGqFU1S3nGMcQATfy6TUuUZwBlzTQ1EXgaeOkYdb5yzl1SjnaIVNyXj8IXf/VuIW2eAte+B/vWwRs/hdxMiGkCo16A1r3gxR/C/k3eOIRhv4Zh98HrP4Z1M7xYXc+Dqyd5t6dGKmb3CyL0h6wb0g+n8/MZP2dVmneD5VXdr+L+Qffz+69/z3sb3gPglFan8Pz5z9MkpkkkmxpRZSYG59yXwJdmNtE5t6UiwZ1zs8ws5TjbJlI5GTvgi78Vjy/Yvxm+esz7Bl54O2JuJnz0G+h8tncAB6/+rEchvmXxARxg/aew8IXKxWxcyZhKDJXy2urXipICwJtr36RXi15FSQFg6d6lTFk7hetOui4CLawZykwMZvY+4PznQa875yp7X9cgM1sC7ADuc86tCFXJzG4CbgLo2LFjJX+l1AsHU8HlB5alb4eM78sucwWwd01wzL1rKxdzz9oQMdeUP6ZUys6snUFlJRfpKZSalVodzamxytP5/BjwD2ATcAj4j//IBEL2HVTAIqCTc+5UvI7sd45W0Tk33jnX3znXPykpqZK/VuqFtn2hRZfAspOuhD5XlF3WPAUG3gRRscVlUTEw4OeVizng5yFi3lT+mFIpF6ZcGLDdLLYZ1/a+lqbRxVfJDQuqV99U5HbVWc65YWWVhdgvBfjAOXdSOX7HZqC/c27vserpdlUptwPb4Kt/eGMOTroS+v4Y8nK8a/pb50GHgd7azNGNYPEkWD4VEpNh6L3QrKM3+d28ZwEHZ9wKnQZFPqZUymdbP+PtdW+TEJvADSfdQJdmXViTtoaJKyaSmZfJ6O6jGdq+bk6fHo5xDKuAi51zG/3tzsA051yvMvZL4SiJwcza4E214cxsIDAF7wzimI1SYhARqbjyJoaKLNTzS+ALM9vob6cAN5fRiEnAcKCVmW0H/gREAzjnnsO7q+lWMzuCd5nq6rKSgoiIhFe5E4Nz7iMz6wYUjhVf7Zw7XMY+Y8t4/Wm821lFaoaDuyAuIfCSzaEDgINGzYvL8g55YwuanlBcVlDgdXg3betNh1EVMaXaZOVlkZufS/O45mVXruPKc1fSOc65z0JMmNfFzHDOvRWmtolUn+w0mDwOtnwNsQlwwf+D06+FaffBwongHPT7KVz0D1jyGnz0f97sqZ0Gw+iXIX0rvHEtHNgKiR1h9ERo3rlyMRu3jPAfpf54dvGz/G/Z/8gryOOClAv4y5C/EBMVE+lmRUx5zhjOBj4DfhjiNQcoMUjt99U/vAM4eAfnafdBw1iY/9/iOgsmQPuB8ME9kO+fLG+ZDbP+DlvneEkBvCTx3l1w4tmViznyb+F9zwLAin0r+PeSfxdtf7z5YwacMIAxPcdEsFWRVZ4Bbn/yf14f/uaIRMjuUkuN5Od6dwOVtnVe8QG8aN+VsHt1cFmT1oFlFY0p1WL9/uBxDOsOrItAS2qOck+iZ2YbzOxVM7vFzHqHs1Ei1a7b+YHbjZO8W0ZLrqeAeWVNSvUBdLsgeP9QZY2ToO81IWKODR1TqsUZbc8gukF0QNmw9se8C7/Oq8hdSb2BM4ChwGNm1hNY4py7PCwtE6lOA2/2On4Lxxyc+ydo1xeuegFmPwk4OOsX0PEMuGYKfPpA8ZiDM2/1EkZcYvGYgwse9jqWyxXzzNAxpVq0adyGp899mueXPE9mXiZjeoyp94mhIuMYGgID8PochgAtgaXOuWPeshoOGscgIlJx4RjHkAEsAx4H/uOc23e8jRMRkZqrIgv1jAVmAbcBr5vZg2Z2bniaJSIikVLuxOCce9c59yu80c7TgOuAD8LULpGKm/0veCTFe3z9T69s3afw5OnwUBK8dTPkZkPaJnjhIniwBUwYAWkbvcFlb98KD7WGf/WFtTNqf0yR41SRPoapQF9gPfCV//jGOZcTvuaFpj4GCbLpK3ix1HpPY1+HqT+H3IPFZcN+5a1zUDi+AKDjIG/thC9LjBuIbgyjJsCkUveyhyXmJJh6U9XGvPZdOHE4IiWFo4/hb8Ai50pPHF/0C893zn1SgXgiVWf7t8Fla6YHHmwBtn0TXHfbN8GzluZlwZppVR9z7fQQMT+q+pjbvlVikONWkUtJ84+WFHyPVEF7RI5PhzODy3pc5E1FUbpehzNClJXaP6YJ9Awx2L+yMXtcHCLmyKqPWXpfkQqoSOdzWYKXdxOpLimDvbmI4lt5S3Ke/2foMQKumgitukPDRt7gsqH3wGXPQMpQaBANnYbAj56FwXfBaT/x6rXsBle9CN3PD0PMC0LEHFn1MU88O8IfiNRm5e5jKDOQ2SLn3OlVEqwM6mMQEam48vYxVOUZg4iI1AFVmRg2V2EsERGJkPKsx1B6HYYAhesxOOeOWU+kVlo+1RsjAHDWnXDyKNixuHheoz5XwPDfegvvzPh98VxJF/4FGrWALx+B5VMgIRnOfxDanRY6pkgNUp7bVUOtw1BI6zFI3bVjMUz5Gd4/c2DqjZDY3lt8J2u3VzbrUW91ti1zYc2HXtn+TZCTHjjmYN96eGUUXD0pOGaLzpDcrzrfmcgxlWc9Bq3DIPXThpkUHcDBe754UnFSKLTuE9g6N7gsPzewLHsvLHk1OOb6z5QYpEapUB+DmV1sZr82s/sLH+FqmEjEte4TXNZpEETFBpad0Adal1qi5ITewWVRMd6ynaWdoOVNpGapyEI9zwFjgF/gjVm4CugUpnaJRF73C2HgTdCgofcYcCOcMgZ++IS39gJ44wyG/Qp++C9onuKVNesEP3wSht0Hnf15/WMT4eLH4eSrgmP2uCgib0/kaCoyV9JS59wpJX42Ad5yzlX7UlMaxyDVKifd+1mYDADycuDwQWiSVFzmHBzc6a3G1qDEd67MPRDbFKLjjh1TJMzCMVfSIf9ntpm1A/YBnY+ncSK1SqiDd3Rc4IEewAwS2gbXLZk8jhVTpIaoSGL4wMyaAX8HFuH1oP03LK0SEZGIqUhieNQ5dxiYamYfAHFAtU+5LRJxB7bCrL9D+nZvHMPp47x1Er56HLbN8yawG3IPxMTDd6944xYSkr2+iObqlpOaryKJYS5wOoCfIA6b2aLCMpF6oSAfXrrMWzQHYMNn3s+tc2Hxq97zTbPgwDZvIrt3by/ed9Ms+MUiiKrIfzuR6leekc9tgGSgkZmdRvEsqglAfBjbJlLz7FhcnBQKrXjLG+BWuiy71LLoB7bAjkXeyGiRGqw8X10uxFvGsz3weInyDOB3YWiTSM2V0BYsCkouTZLYAZpth71rS5V1CNzXGkBCu+ppp0gllGfk84vAi2Z2pXNuajW0SaTmSmgHP/g/+PyvXnJocaI3XmHfenjjp3A4A2KawshHoXVP2PglpG3wksnZv/Gm1BCp4SoyjqEN8DDQzjk30sx6A4Occ/8LZwND0TgGibiMVMjYAe36QoMor+xwJuxeCa17eeMWwOuTSF0MTdvqbEEiLhzrMbwAfAwU/uteC9x9HG0Tqf0S2kL7fsVJASC2idd/UJgUwHs9uZ+SgtQqFUkMrZxzbwAFAM65I8Cx1oDGzCaY2W4zW36U183MnjSz9Wa21Mx0h5OISIRV5L65LDNriT81pJmdCaSXsc9E4GngpaO8PhLo5j/OAP7t/xSpfhu/9MYcJLaHgT+HRs1h73pYMMF7vf/10Kqbt/bC/P94t6T2uRy6/AAKCrzbVbfNg/YD4bRx3rQYlYkpEiEV6WM4HXgK6AOsAJKAUc65pWXslwJ84Jw7KcRrzwNfOOcm+dtrgOHOudRjxVQfg1S5NdNh0liKpsRue6q3dsKzg+Cw//0nNgFunQNvXOvddlpojJ8Q5jxVXHbmbd4EepWJ2euScL1bqafCMVfSSuBtIBs4CLyD189QGcnAthLb2/2yYyYGkSq36CUC1klIXQJzny4+gIN3x9G8ZwIP4IX7ll6PYeGLsH9z+WLOPUpMJQaJkIr0MbwE9AT+gnfm0A14uZK/30KUhTyFMbObzGyBmS3Ys2dPJX+tSCmhJrVrHGLyu/ijTIhXev9QZUeLGapMk+xJBFUkMfRwzt3onPvcf9wEdK/k798OlBwF1B7YEaqic268c66/c65/UlKI/0gilTH4bu/6f6HTr4UzbvEu/xRqczKceQv0K7GoYVwzGHI3nHu/N4ANvJ/n3l/5mCIRUpE+honAc865ef72GcBPnXO3lbFfCkfvY7gYuAO4CK/T+UnnXJnzBaiPQcIiJ92b+yihPXQY4JXlH4GNn3trLXQ5p3ieo+0LvMn0upwDjZp5Zfs3e+XJ/bx1nKsipkgVKm8fQ0USwyqgB7DVL+oIrMK7fdU5504Jsc8kYDjQCtgF/AmIxtvhOTMzvLuWRuD1XVzvnCvziK/EICJSceHofB5R0UY458aW8boDbj9WHRERqV7lTgzOuS3hbIiIiNQMFel8FhGRekCJQUREAigxiIhIACUGEREJoMQgIiIBlBhERCSAEoOIiARQYhARkQBKDCIiEkCJQUREAigxiIhIACUGEREJoMQgIiIBlBhERCSAEoOIiARQYhARkQBKDCIiEkCJQUREAigxiIhIACUGEREJoMQgIiIBlBhERCSAEoOIiARQYqhh9mUeJiMnL9LNEJF6rGGkGyCe3CMF/HLSwu0iAAAR5UlEQVTyYqYtTyW6QQN+Pqwzv7qwZ6SbJSL1kM4Yaog3Fmzjw2WpOAe5+QU88/kGvtu6P9LNEpF6SImhhli/OzOobN2u4DIRkXBTYqghhvdICtiOiWrA4G6tItQaEanP1MdQQwzv0ZpHrjyZl+dtIT66Ib84tyvJzRpFulkiUg8pMdQgYwZ0ZMyAjpFuhojUc7qUJCIiAcKeGMxshJmtMbP1ZvbbEK9fZ2Z7zGyx/7gx3G0SEZGjC+ulJDOLAp4Bzge2A/PN7D3n3MpSVSc75+4IZ1tqOuccf5u+2utjiGnIPed358dn6LKSiFS/cJ8xDATWO+c2OudygdeBy8L8O2uldxfv4PlZG8nOzWdv5mF+9/Yy1uw8GOlmiUg9FO7EkAxsK7G93S8r7UozW2pmU8ysQ6hAZnaTmS0wswV79uwJR1sjalGIwWyLt2mAm4hUv3AnBgtR5kptvw+kOOdOAT4FXgwVyDk33jnX3znXPykpKVSVWm1ASouAbTPo16l5hFojIvVZuBPDdqDkGUB7YEfJCs65fc65w/7mf4B+YW5TjXTJKW35xTldaRYfTbvEOB698hS6tm4a6WaJSD0U7nEM84FuZtYZ+B64GvhxyQpm1tY5l+pvXgqsCnObaiQz494LenDvBT0i3RQRqefCmhicc0fM7A7gYyAKmOCcW2FmfwYWOOfeA+40s0uBI0AacF042yQiIsdmzpW+5F/z9e/f3y1YsCDSzRARqVXMbKFzrn9Z9TQlRhWas34v//hkLQeycxndvwM3n92FbWnZPPTBSlbtzGBI1yR+f3EvGjYw/jZ9NZ+t3k2XpMb84ZLedElqwstzN/PS3C3ExzbkrnO7ck7PEyodU0SkonTGUEX2ZR5m8COfkZNXUFT2xJi+TJi9iaXb04vKrh7QgYRG0YyftbGo7MRWjfn9xT352YsLi8qio4ypt57F6OfnHnfMmfeejVmoG8NEpD7SGUM1+3ZTWsABHOCTlbsCDuAAs9buoWlcdEDZxr1ZfLg0NaAsL9/x5oLtIWLuLHfMbWmH6Ngy/rjej4jUX5pEr4r0aNOU0l/OT05OpF1iXFC9nm0Db0NtHh9N347BYxYGdWlZqZitE2Ir+C5ERJQYqsyJSU34/UW9aBwThRmM6NOG6wan8NjoU2mT4B3Ie7Zpyp9+2IffjuzJqR2aAdCqSSx/H3UqYwd25IrTkmlgEBfdgF+e152LTm4bImbncseMi46KzB9DRGo19TFUsZy8fA7nFZAYX3xpJ7/AkZaVS1LTwG/wezMP06xRNA2jivNz+qE8oqOM+JiGVRZTRATUxxAxcdFRQd/UoxpY0AEcvG/2pSU2ig4qq2xMEZGK0NdKEREJoDOGKrRm50Ge/WI9+7PzGNO/Axef0pYD2bk8OXM9K1PTGdotiZuGnUiUGRNmb2Lmqt10bd2EO8/tRlLTWGau2sUr/noMt5zdhZPbJ1Y6pohIRSkxVJGDOXlcPX4u+7PzAO8W0viYAUyYvYmv1u0FYN7GNDIO5ZHQKJq/f7wGgLkb97F0+wH+cElvbnxpAYVdPl+s2c0Hdw6tVMx37xhSnX8CEakjlBiqyJwN+4oO4IXe/u77ogN4oQ+WppJQqh9hyfZ0Js/fSsn7ALJy85k4e1NQzLcWlT/mtrRsOrTQOAYRqRj1MVSR9s0bBZV1ahlPi8YxQfVK120cE0WXpOAptnu2TahUzNL1RETKQ4mhivRpl8j1g1OKBqSdnJzIz4Z05oFL+xAX7f2ZWzWJ4XcX9eJXF/agrT9ILaZhA/5wSW+uHdSJgSUW67mqX3vGDuwYFPPGoeWP2ThWJ4QiUnEax1DFtu/PJv1QHn3aJRaVpWfnsXFvJr3bJRDb0LvtNC+/gBU7MujYIvAMYPXODOKjGwZMZVHZmCIiUP5xDEoMIiL1RHkTgy4liYhIgDp7EfrDpd9z5+tLyC9wtEmI5fzebYiPieLas1JIbtaI3Rk5vDh3M/uz87jy9Pb069Scw0fyeXXeVlamZjC0Wysu65sMwEfLdzJz1S66tm7CuEGdiI9pyPLv05k8f1u9jhltBbyzZCf7s/NoGteQz+4dSqumugtKpLars5eSUn77YcjypKaxTLtzCJc/O4ft+w8B3vQSb9x8JhPnbOH9JTuK6v5mRE8SGjXk928vLyo7u3sSvx3Zk8uemU3ukYJ6H7MkM9j014tD/t1FJPLq9VxJ10345qiv7Tl4mPGzNhYdGMGbkO61b7by4dIdAXUnz98atM7Bl2v30K5ZXMCBsT7HLMk52JmeTZtEnTWI1GZ1so+hW+tjL2mZFGKiuWbxMTQqNVFdYqPooEntYqIa0DLEHT/VFbN5hWIG7x+OmCUlRAdPAigitUudTAy/v6TPUV8b3LUlPxt6Ihf0PqGorG1iHDcO7cw9F/QoKotp2IB7LujB3ed1Iz6m+KB56/Au3DDkRFJK3E5anTF/VqGYncMes6Tm8dHExysxiNR2dbaPAWDs+Hms232QBy/tTVx0QxrFRDHoxJZF6yDP35zG/qxchnVPKprWesOeTFalZjCwcwtaN/UGjKVl5TJ3wz66tG5MzzbeaOTDR/L5et3eeh9z+fYDvDh3C5ed2o5fj+x1HJ+miFQXjWMQEZEAGscgIiLHpU7elRQp2blHeOe7HRw4lMsPT2lHhxbxOOeYsXIXq1IzGNK1Ff39+ZCWbj/A56v30KV1Y0ae1JaoBkZq+iHeXbyDxjFRXHZaMglx0RWKKSJSFXQpqYrkFzgue+Zrln+fAUB8TBRv3zaYSd9uZeKczUX1Hh11Ck1jG3Lba4uKptm+4vRk7j63O5c89RUZOUcAODGpMe/fMYQx4+eWK+bo/h2q5X2KSO1Vr8cxRMKcDXuLDuAA2bn5TJyziSkLtwfU+8+sjSQ0ig5Ye+Ht774nsVHDoqQAsHFPFv/+YkNQzBdmb2LqouCYSgwiUlXUx1BFGhTOjV2qzEqVNzCjQamqBkRZ8EcRFeLTiTJCxhQRqSpKDFVk0IktOa1js6LtprENuX5wZ64/K6WozMwbC3DzsC5ElcgOYwZ04LrBKQFTZfds05Rbzu4SHHPIiSFjiohUFfUxVKGcvHymL09lf1YeF53cljb+wjmz1u5hpd9RfFKyt6bC2l0H+Xz1brq2bsI5PVtjZuzNPMyHS1OJj4ni4lPaEh/TsEIxRUSOReMYREQkQI0Zx2BmI8xsjZmtN7Pfhng91swm+69/Y2Yp4W6TiIgcXVgTg5lFAc8AI4HewFgz612q2s+A/c65rsA/gUfC2SYRETm2cJ8xDATWO+c2OudygdeBy0rVuQx40X8+BTjXSt92IyIi1SbciSEZ2FZie7tfFrKOc+4IkA60DHO7RETkKMKdGEJ98y/d212eOpjZTWa2wMwW7Nmzp0oaJyIiwcKdGLYDJYfktgd2HK2OmTUEEoG00oGcc+Odc/2dc/2TkpLC1FwREQl3YpgPdDOzzmYWA1wNvFeqznvAT/3no4DPXG28h1ZEpI4I+zgGM7sIeAKIAiY45x42sz8DC5xz75lZHPAycBremcLVzrmNZcTcA2wJa8MjqxWwN9KNkOOmz6/2quufXSfnXJmXXGrlALe6zswWlGcQitRM+vxqL312Hs2VJCIiAZQYREQkgBJDzTQ+0g2QStHnV3vps0N9DCIiUorOGEREJIASQ4SZ2XVm1i7S7ZDjZ2Z/NrPzjmO/4Wb2QTjaVF+ZWTszm3Ic+/03xASfpevcYmbXHn/rag9dSoowM/sCuM85pwUmajB/YkdzzhVUYczheJ/9JeWs39CfT0wqSH+7itEZQxiYWWMz+9DMlpjZcjMbY2b9zOxLM1toZh+bWVszGwX0B141s8Vm1sjMzjWz78xsmZlNMLNYP+bfzGylmS01s8f8sh/6a1h8Z2afmtkJkXzftYGZPWJmt5XYfsDM7jWzX5nZfP/v+6D/WoqZrTKzZ4FFQAczm+h/psvM7Jd+vYn+Z4mZDTCzOf5n/62ZNTWzODN7wd/nOzP7QYh2tTCzd/zfP8/MTinRvvFmNgN4qRr+RLXGMT7L5f72dWb2ppm9D8wwswZm9qyZrTCzD8xsWonP7Qsz6+8/zzSzh/3PcF7h/ys//n3+867+/7klZrbIzLqYWRMzm+lvLzOz0jNJ1x7OOT2q+AFcCfynxHYiMAdI8rfH4I0CB/gC6O8/j8Obaba7v/0ScDfQAlhD8RleM/9n8xJlNwL/iPR7r+kPvBH2X5bYXglci3c3iuF9WfoAGAakAAXAmX7dfsAnJfYt/Bwm4k3nEgNsBAb45QlAQ+Be4AW/rCew1f+shwMf+OVPAX/yn58DLPafPwAsBBpF+m9X0x5H+SyHAcv97evw5mJr4W+PAqb5n3EbYD8wyn+t5P9DB/zQf/4o8IcSn8V9/vNvgMv953FAvP9ZJ/hlrYD1hf8/a9ujIRIOy4DHzOwRvIPMfuAk4BPvigRRQGqI/XoAm5xza/3tF4HbgaeBHOC/ZvahHxO8SQknm1lbvIPSpvC8nbrDOfedmbX2+3WS8D6bU4ALgO/8ak2AbngH8C3OuXl++UbgRDN7CvgQmFEqfA8g1Tk33/9dGQBmNgTvwI9zbrWZbQG6l9p3CN4XCpxzn5lZSzMrXMz7Pefcocq/+7rlKJ/l1lLVPnHOFU7KOQR403mXA3ea2edHCZ1L8f+xhcD5JV80s6ZAsnPubb8dOX55NPAXMxuG94UiGTgB2FmJtxkRSgxh4Jxba2b9gIuAvwKfACucc4PK2DXkAkXOuSNmNhA4F28iwjvwvlU+BTzuvDmnhuN9o5GyTcH79tgGb/GoFOCvzrnnS1Yyb5nZrMJt59x+MzsVuBAvYY8Gbii5CyGmjOcon2s56hTGygrxmnhKf5allfzblXcBsDznf+0H8gk+Th4tzjV4Caqfcy7PzDbjnU3UOupjCAP/G0y2c+4V4DHgDCDJzAb5r0ebWR+/+kGgqf98NZBiZl397XHAl2bWBEh0zk3Du7TU1389Efjef144Q62U7XW8BDsK78DyMXCD/3fGzJLNrHXpncysFdDAOTcV+CNweqkqq4F2ZjbAr9/UvKnkZ+EdNDCz7kBHvEuDJZWsMxzYW3jGIcdU+rM8lq+BK/2+hhPwLuVVmP+5bDezH0HRuvXxeP8fd/tJ4QdAp+OJXxPojCE8Tgb+bmYFQB5wK3AEeNK/PNAQb8bZFXjXp58zs0PAIOB64E3/gDIfeA6vj+Fd82aiNeCX/u95wK/7PTAP6Fwt766Wc86t8C8HfO+cSwVSzawXMNe/1JcJ/ATv22JJycALZlb4her/SsXNNbMxwFNm1gg4BJwHPIv3GS/D+3dwnXPusAWuYPuAH3spkI0SfbmU/iz9s7yjmYp31r0cWIvXT5B+nL96HPC8eTNF5wFXAa8C75vZAmAx3heFWkm3q4pIvWFmTZxzmWbWEvgWGOycq3V9AOGmMwYRqU8+MLNmeDdrPKSkEJrOGEREJIA6n0VEJIASg4iIBFBiEBGRAEoMImHmz8nTLNLtECkvdT6LiEgAnTGIcNQZcTf7M3h+6z+6+nWTzGyqebOxzjezwX55EyueRXWpmV3pl2/2R01jZj/xYy02s+fNLMp/BM3aKhIpGscg4hkB7HDOXQzgj1B/BMhwzg00b4GWJ4BLgH8B/3TOfW1mHfGm1OiFN01GunPuZD9G85K/wB9dPQZvUFWeedN5X4M3Aj7ZOXeSX0+XnSSilBhEPAEz4jrnvvKnrJjkvz4J+Kf//Dygd4kpLRL8aRnOw5u3B/Am3Sv1O87Fm7p7vr9vI2A38D7HnrVVpFopMYgQPCOueQvjQOBsqYXPGwCDSk+Fbd7R/liddga86Jz7v6AXjj1rq0i1Uh+DCCFnxC2cOXVMiZ9z/ecz8KY+L9y371HKAy4lATOBUYUzt5q3aluncszaKlKtdMYg4gk1I+4UINbMvsH7EjXWr3sn8Iw/E2rhtNq3AP/PL1+ONzPrg8Bbhb/AObfSzP6Av8yk/3tux5uF9aiztopUN92uKnIU/kIr/Z1zeyPdFpHqpEtJIiISQGcMIiISQGcMIiISQIlBREQCKDGIiEgAJQYREQmgxCAiIgGUGEREJMD/B5m/2qK76rAWAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.swarmplot(x = 'species', y = 'petal_width', data = iris)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Histogram of all measurements across all species.\n",
    "iris.hist(figsize = (8, 6))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>sepal_length</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.109369</td>\n",
       "      <td>0.871754</td>\n",
       "      <td>0.817954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sepal_width</th>\n",
       "      <td>-0.109369</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.420516</td>\n",
       "      <td>-0.356544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>petal_length</th>\n",
       "      <td>0.871754</td>\n",
       "      <td>-0.420516</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.962757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>petal_width</th>\n",
       "      <td>0.817954</td>\n",
       "      <td>-0.356544</td>\n",
       "      <td>0.962757</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              sepal_length  sepal_width  petal_length  petal_width\n",
       "sepal_length      1.000000    -0.109369      0.871754     0.817954\n",
       "sepal_width      -0.109369     1.000000     -0.420516    -0.356544\n",
       "petal_length      0.871754    -0.420516      1.000000     0.962757\n",
       "petal_width       0.817954    -0.356544      0.962757     1.000000"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Correlations between measurements.\n",
    "iris.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualising correlations with a heatmap.\n",
    "sns.heatmap(iris.corr(), annot = True, cmap = 'RdYlGn_r') \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 444.75x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Closer look at scatter plots for petal measurements.\n",
    "sns.FacetGrid(iris, hue = 'species', height=5).map(plt.scatter, 'petal_length', 'petal_width').add_legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 444.75x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Closer look at scatter plots for sepal measurements.\n",
    "sns.FacetGrid(iris, hue = 'species', height=5).map(plt.scatter, 'sepal_length', 'sepal_width').add_legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Splitting the Dataset \n",
    "Below the dataset is split to explore each species individually."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating three smaller datasets, one for each species, so they can be individually assessed.\n",
    "setosa = iris.loc[0:49]\n",
    "versicolor = iris.loc[50:99]\n",
    "virginica = iris.loc[100:149]\n",
    "\n",
    "# Dropping the fifth column 'species' as not required and interferes with creating histograms.\n",
    "setosa = setosa.drop(columns = 'species')\n",
    "versicolor = versicolor.drop(columns = 'species')\n",
    "virginica = virginica.drop(columns = 'species')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Means and Standard Deviations\n",
    "Examination of means and standard deviations of each species. Comparison with one another and the whole. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>species</th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>setosa</td>\n",
       "      <td>5.006000</td>\n",
       "      <td>3.418</td>\n",
       "      <td>1.464000</td>\n",
       "      <td>0.244000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>versicolor</td>\n",
       "      <td>5.936000</td>\n",
       "      <td>2.770</td>\n",
       "      <td>4.260000</td>\n",
       "      <td>1.326000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>virginica</td>\n",
       "      <td>6.588000</td>\n",
       "      <td>2.974</td>\n",
       "      <td>5.552000</td>\n",
       "      <td>2.026000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>all_species</td>\n",
       "      <td>5.843333</td>\n",
       "      <td>3.054</td>\n",
       "      <td>3.758667</td>\n",
       "      <td>1.198667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       species  sepal_length  sepal_width  petal_length  petal_width\n",
       "0       setosa      5.006000        3.418      1.464000     0.244000\n",
       "1   versicolor      5.936000        2.770      4.260000     1.326000\n",
       "2    virginica      6.588000        2.974      5.552000     2.026000\n",
       "3  all_species      5.843333        3.054      3.758667     1.198667"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Mean values of each individual iris species and dataset as a whole.\n",
    "sp_mean = iris.groupby('species').mean()\n",
    "to_mean = iris.mean()\n",
    "means = sp_mean.append(to_mean, ignore_index=True)\n",
    "means.insert(0, 'species', ['setosa', 'versicolor', 'virginica', 'all_species'])\n",
    "means"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>species</th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>setosa</td>\n",
       "      <td>0.352490</td>\n",
       "      <td>0.381024</td>\n",
       "      <td>0.173511</td>\n",
       "      <td>0.107210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>versicolor</td>\n",
       "      <td>0.516171</td>\n",
       "      <td>0.313798</td>\n",
       "      <td>0.469911</td>\n",
       "      <td>0.197753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>virginica</td>\n",
       "      <td>0.635880</td>\n",
       "      <td>0.322497</td>\n",
       "      <td>0.551895</td>\n",
       "      <td>0.274650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>all_species</td>\n",
       "      <td>0.828066</td>\n",
       "      <td>0.433594</td>\n",
       "      <td>1.764420</td>\n",
       "      <td>0.763161</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       species  sepal_length  sepal_width  petal_length  petal_width\n",
       "0       setosa      0.352490     0.381024      0.173511     0.107210\n",
       "1   versicolor      0.516171     0.313798      0.469911     0.197753\n",
       "2    virginica      0.635880     0.322497      0.551895     0.274650\n",
       "3  all_species      0.828066     0.433594      1.764420     0.763161"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Standard deviation values of each individual iris species and dataset as a whole.\n",
    "sp_std = iris.groupby('species').std()\n",
    "to_std = iris.std()\n",
    "std = sp_std.append(to_std, ignore_index=True)\n",
    "std.insert(0, 'species', ['setosa', 'versicolor', 'virginica', 'all_species'])\n",
    "std"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Setosa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>50.00000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>50.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5.00600</td>\n",
       "      <td>3.418000</td>\n",
       "      <td>1.464000</td>\n",
       "      <td>0.24400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.35249</td>\n",
       "      <td>0.381024</td>\n",
       "      <td>0.173511</td>\n",
       "      <td>0.10721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>4.30000</td>\n",
       "      <td>2.300000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.10000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4.80000</td>\n",
       "      <td>3.125000</td>\n",
       "      <td>1.400000</td>\n",
       "      <td>0.20000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>5.00000</td>\n",
       "      <td>3.400000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>0.20000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>5.20000</td>\n",
       "      <td>3.675000</td>\n",
       "      <td>1.575000</td>\n",
       "      <td>0.30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.80000</td>\n",
       "      <td>4.400000</td>\n",
       "      <td>1.900000</td>\n",
       "      <td>0.60000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       sepal_length  sepal_width  petal_length  petal_width\n",
       "count      50.00000    50.000000     50.000000     50.00000\n",
       "mean        5.00600     3.418000      1.464000      0.24400\n",
       "std         0.35249     0.381024      0.173511      0.10721\n",
       "min         4.30000     2.300000      1.000000      0.10000\n",
       "25%         4.80000     3.125000      1.400000      0.20000\n",
       "50%         5.00000     3.400000      1.500000      0.20000\n",
       "75%         5.20000     3.675000      1.575000      0.30000\n",
       "max         5.80000     4.400000      1.900000      0.60000"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Setosa descriptive statistics.\n",
    "setosa.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Histograms displaying distribution of setosa data.\n",
    "setosa.hist(figsize = (8, 6))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>sepal_length</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.746780</td>\n",
       "      <td>0.263874</td>\n",
       "      <td>0.279092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sepal_width</th>\n",
       "      <td>0.746780</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.176695</td>\n",
       "      <td>0.279973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>petal_length</th>\n",
       "      <td>0.263874</td>\n",
       "      <td>0.176695</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.306308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>petal_width</th>\n",
       "      <td>0.279092</td>\n",
       "      <td>0.279973</td>\n",
       "      <td>0.306308</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              sepal_length  sepal_width  petal_length  petal_width\n",
       "sepal_length      1.000000     0.746780      0.263874     0.279092\n",
       "sepal_width       0.746780     1.000000      0.176695     0.279973\n",
       "petal_length      0.263874     0.176695      1.000000     0.306308\n",
       "petal_width       0.279092     0.279973      0.306308     1.000000"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Setosa correlations.\n",
    "setosa.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Setosa correlation heatmap.\n",
    "sns.heatmap(setosa.corr(), annot=True, cmap='RdYlGn_r') \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Versicolor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>50.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>50.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5.936000</td>\n",
       "      <td>2.770000</td>\n",
       "      <td>4.260000</td>\n",
       "      <td>1.326000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.516171</td>\n",
       "      <td>0.313798</td>\n",
       "      <td>0.469911</td>\n",
       "      <td>0.197753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>4.900000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>5.600000</td>\n",
       "      <td>2.525000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>5.900000</td>\n",
       "      <td>2.800000</td>\n",
       "      <td>4.350000</td>\n",
       "      <td>1.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.300000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>4.600000</td>\n",
       "      <td>1.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>7.000000</td>\n",
       "      <td>3.400000</td>\n",
       "      <td>5.100000</td>\n",
       "      <td>1.800000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       sepal_length  sepal_width  petal_length  petal_width\n",
       "count     50.000000    50.000000     50.000000    50.000000\n",
       "mean       5.936000     2.770000      4.260000     1.326000\n",
       "std        0.516171     0.313798      0.469911     0.197753\n",
       "min        4.900000     2.000000      3.000000     1.000000\n",
       "25%        5.600000     2.525000      4.000000     1.200000\n",
       "50%        5.900000     2.800000      4.350000     1.300000\n",
       "75%        6.300000     3.000000      4.600000     1.500000\n",
       "max        7.000000     3.400000      5.100000     1.800000"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Versicolor descriptive statistics.\n",
    "versicolor.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Histograms displaying distribution of versicolor data.\n",
    "versicolor.hist(figsize = (8, 6))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>sepal_length</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.525911</td>\n",
       "      <td>0.754049</td>\n",
       "      <td>0.546461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sepal_width</th>\n",
       "      <td>0.525911</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.560522</td>\n",
       "      <td>0.663999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>petal_length</th>\n",
       "      <td>0.754049</td>\n",
       "      <td>0.560522</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.786668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>petal_width</th>\n",
       "      <td>0.546461</td>\n",
       "      <td>0.663999</td>\n",
       "      <td>0.786668</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              sepal_length  sepal_width  petal_length  petal_width\n",
       "sepal_length      1.000000     0.525911      0.754049     0.546461\n",
       "sepal_width       0.525911     1.000000      0.560522     0.663999\n",
       "petal_length      0.754049     0.560522      1.000000     0.786668\n",
       "petal_width       0.546461     0.663999      0.786668     1.000000"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Versicolor correlations.\n",
    "versicolor.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Versicolor correlation heatmap.\n",
    "sns.heatmap(versicolor.corr(), annot=True, cmap='RdYlGn_r') \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Virginica"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>50.00000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>50.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>6.58800</td>\n",
       "      <td>2.974000</td>\n",
       "      <td>5.552000</td>\n",
       "      <td>2.02600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.63588</td>\n",
       "      <td>0.322497</td>\n",
       "      <td>0.551895</td>\n",
       "      <td>0.27465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>4.90000</td>\n",
       "      <td>2.200000</td>\n",
       "      <td>4.500000</td>\n",
       "      <td>1.40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>6.22500</td>\n",
       "      <td>2.800000</td>\n",
       "      <td>5.100000</td>\n",
       "      <td>1.80000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>6.50000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>5.550000</td>\n",
       "      <td>2.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.90000</td>\n",
       "      <td>3.175000</td>\n",
       "      <td>5.875000</td>\n",
       "      <td>2.30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>7.90000</td>\n",
       "      <td>3.800000</td>\n",
       "      <td>6.900000</td>\n",
       "      <td>2.50000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       sepal_length  sepal_width  petal_length  petal_width\n",
       "count      50.00000    50.000000     50.000000     50.00000\n",
       "mean        6.58800     2.974000      5.552000      2.02600\n",
       "std         0.63588     0.322497      0.551895      0.27465\n",
       "min         4.90000     2.200000      4.500000      1.40000\n",
       "25%         6.22500     2.800000      5.100000      1.80000\n",
       "50%         6.50000     3.000000      5.550000      2.00000\n",
       "75%         6.90000     3.175000      5.875000      2.30000\n",
       "max         7.90000     3.800000      6.900000      2.50000"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Virginica descriptive statistics.\n",
    "virginica.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Histograms displaying distribution of virginica data.\n",
    "virginica.hist(figsize = (8, 6))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>sepal_length</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.457228</td>\n",
       "      <td>0.864225</td>\n",
       "      <td>0.281108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sepal_width</th>\n",
       "      <td>0.457228</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.401045</td>\n",
       "      <td>0.537728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>petal_length</th>\n",
       "      <td>0.864225</td>\n",
       "      <td>0.401045</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.322108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>petal_width</th>\n",
       "      <td>0.281108</td>\n",
       "      <td>0.537728</td>\n",
       "      <td>0.322108</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              sepal_length  sepal_width  petal_length  petal_width\n",
       "sepal_length      1.000000     0.457228      0.864225     0.281108\n",
       "sepal_width       0.457228     1.000000      0.401045     0.537728\n",
       "petal_length      0.864225     0.401045      1.000000     0.322108\n",
       "petal_width       0.281108     0.537728      0.322108     1.000000"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Virginica correlations.\n",
    "virginica.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Virginica correlation heatmap.\n",
    "sns.heatmap(virginica.corr(), annot=True, cmap='RdYlGn_r') \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
